Implementing ‘quality assurance procedures’ in monetary and financial statistics (MFS) Q European conference on quality in statistics Vienna, 3 June 2014 Violetta Damia Jean-Marc Israël European Central Bank Directorate General Statistics Monetary and Financial statistics Division ECB-PUBLIC

Rubric © Overview Implementing ‘quality assurance procedures’ in monetary and financial statistics Example 1. Enhancing MFS methodological soundness Example 2. Revision analysis MFS - Quality assurance procedures 4 5Foreseen initiatives for Example 3. “Top-down” analysis for balance sheet data ECB-PUBLIC [Please select]

Rubric © Input: data collected from reporting agents by the NCBs and reported to the ECB –methodologically sound data –in line with internationally accepted standards and classifications –ECB regulations & Guidelines set common harmonised standards –according to a fixed and agreed timetable Throughput: several quality checks on the national contributions received –completeness, internal and intra-period consistency –external consistency –Revision studies –Plausibility checks Output: data accessibility & dissemination policy –press releases –ECB Statistical Data Warehouse and on the ECB’s website Implementing ‘quality assurance procedures’ in monetary and financial statistics 3 ECB-PUBLIC MFS - Quality assurance procedures (1)

Rubric ©Implementing ‘quality assurance procedures’ in monetary and financial statistics 4 ECB-PUBLIC MFS - Quality assurance procedures (2) Main MFS statistical productsMain quality elements Monetary financial institutions balance sheet statistics Legal basis (Regulation or Guideline) Data collection (by NCBs from reporting agents) and coverage (full, modified census or stratification) Methodological sources (compliance with int. statistical standards) Reporting periodicity and transmission deadlines Revision policy Data quality management (quality checks, time series analysis, etc.) Compliance monitoring (~ to legal instrument) Dissemination (advance release calendar, press release, availability on the ECB’s Statistical Data Warehouse and on the ECB’s website, etc.)  MFS ‘hotline’ providing assistance to users on all statistical products. Monetary financial institutions interest rate statistics List of monetary financial institutions (MFIs) Securities issues statistics Payments and securities settlement systems statistics Investment funds balance sheet statistics List of investment funds (IFs) Financial vehicle corporations (FVCs) balance sheet statistics List of financial vehicle corporations (FVCs)

Rubric © Development of MFS ~ meeting user requirements & in line with international statistical standards – also input to other stat. domains Until recently, several deviations with international statistical standards –reporting units and sectors, counterpart sectors or sub-sectors, financial instruments, etc. –other specific issues, e.g. the valuation principles applied, the treatment of accrued interest, and the treatment of non-performing loans. Additional requirements from users  substantial amendment of five ECB Regulations and Guideline on MFS (ECB/2014/15) Regulations ECB/2013/33 on MFI balance sheet statistics, ECB/2013/34 on MFI interest rate statistics, ECB/2013/39 on Post Office Giro Institutions, ECB/2013/38 on Investment Funds and ECB/2013/40 on Financial Vehicle Corporations  1 st reporting in in Jan with data for Dec – publication in mid-2015 Implementing ‘quality assurance procedures’ in monetary and financial statistics 5 Example 1. Enhancing MFS methodological soundness ECB-PUBLIC

Rubric © To evaluate the reliability of first releases Special features –data can be revised at any release –“ordinary revisions” vs. “exceptional” revisions (the latter related to to reclassifications and improved reporting procedures) Revisions of the monthly monetary aggregates and components  differences between the revised period-on-period growth rates at a pre-determined lag and the first release  estimation of bias Implementing ‘quality assurance procedures’ in monetary and financial statistics 6 Example 2. Revision analysis (1) ECB-PUBLIC

Rubric © Revisions to the month-on-month growth rates of M3 to better identify the timing of a given revision Implementing ‘quality assurance procedures’ in monetary and financial statistics 7 Example 2. Revision analysis (2) ECB-PUBLIC Figure 2: Revision of M3 growth rate (2013) (No of occurrences (Y-axis), hundredths of a percentage point (Y-axis)) Revisions to the components of M3 at lag t+3 to understand the largest contributions to the overall M3 revisions

Rubric © Traditionally, a “bottom-up approach” is followed for consistency and plausibility of aggregated series  focus on raw series –vertical checks (TRUE/FALSE type of check) –horizontal checks (based on statistical significance) if developments are correct in raw series, they must be correct in derived aggregates New “top-down approach” for analysis and identification of possible special developments  focus on aggregated series  decomposition of the aggregate into its main underlying components and identification of the raw series responsible of the development Implementing ‘quality assurance procedures’ in monetary and financial statistics 8 Example 3. “Top-down” analysis for balance sheet data (1) ECB-PUBLIC

Rubric © 2-steps procedure Step 1: run horizontal checks on selected aggregate series –better statistical modelling of aggregates –special development in raw series usually matters when impact on aggregate is significant –MFI balance sheet statistics: run checks on country consolidated balance sheet Step 2: Decompose the special development into components –reverse engineer the set of raw series responsible for development –ECB aggregation framework allows for identification of series dependencies in the aggregation tree –User defined threshold, user friendly graphical output Implementing ‘quality assurance procedures’ in monetary and financial statistics 9 Example 3. “Top-down” analysis for balance sheet data (2) ECB-PUBLIC

Rubric © Advantages: –significantly reduce the number of processed series –answers to typical questions such as “is development widespread?; “which are the sectors responsible for it?”, etc –combine checking for outliers with economic interpretation –Step 2 can also be used independently of horizontal checks Implementing ‘quality assurance procedures’ in monetary and financial statistics 10 Example 3. “Top-down” analysis for balance sheet data (3) ECB-PUBLIC

Rubric ©Implementing ‘quality assurance procedures’ in monetary and financial statistics 11 Example 3. “Top-down” analysis for balance sheet data (4) ECB-PUBLIC

Rubric © Several work-streams are in the pipeline to (1)increase MFS availability, and (2)enhance the input to other statistical domains A new Regulation on assets and liabilities of Insurance Corporations A new Regulation on high frequency data on money market activity (MMSRR) The development of an “Analytical Credit dataset” (AnaCredit) across the ESCB the provision of necessary data for the ECB’s financial stability analysis of the euro area and to cover the European Systemic Risk Board (ESRB) needs Implementing ‘quality assurance procedures’ in monetary and financial statistics 12 Foreseen initiatives for ECB-PUBLIC

Rubric ©Implementing ‘quality assurance procedures’ in monetary and financial statistics 13 ECB-PUBLIC